Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
12-2012
Abstract
We present FAME, a comprehensive C# software library package providing soft formation control for large flocks of agents. While many existing available libraries provide means to create flocks of agent equipped with simple steering behavior, none so far, to the best of our knowledge, provides an easy and hassle free approach to control the formation of the flock. Here, besides the basic flocking mechanisms, FAME provides an extensive range of advanced features that gives enhanced soft formation control over multiple flocks. These soft formation features include defining flocks in any user-defined formation, automated self-organizing agent within formation, manipulating formation shape at real-time and bending the formation shape naturally along the curvature of the path. FAME thus not only supports the research studies of collective intelligence and behaviors, it is useful for rapid development of digital games. Particularly, the development cost and time pertaining to the creation of multi-agent group formation can be significantly reduced.
Keywords
soft formation, flock, behavioral animation, collective behavior, games
Discipline
Programming Languages and Compilers | Software Engineering
Research Areas
Data Science and Engineering
Publication
Simulated Evolution and Learning: 9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19: Proceedings
Volume
7673
First Page
258
Last Page
269
ISBN
9783642348587
Identifier
10.1007/978-3-642-34859-4_26
Publisher
Springer
City or Country
Cham
Citation
HO, Choon Sing; ONG, Yew-Soon; CHEN, Xianshun; and TAN, Ah-hwee.
FAME, soft flock formation control for collective behavior studies and rapid games development. (2012). Simulated Evolution and Learning: 9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19: Proceedings. 7673, 258-269.
Available at: https://ink.library.smu.edu.sg/sis_research/6720
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-642-34859-4_26